Response Parsers (maticlib.core.parsers)

Advanced utilities to force LLMs into generating structured, machine-readable data.

Available Parsers

1. PydanticResponseParser: (Recommended) Validates against a Pydantic BaseModel.
2. JSONResponseParser: Extracts a raw Python dictionary from JSON blocks.
3. XMLResponseParser: Extracts data from flat XML tags.

Integration Workflow

You don't need to call the parser manually. Simply pass your model to the client.

from pydantic import BaseModel
from maticlib.llm.openai import OpenAIClient

class Sentiment(BaseModel):
    score: float
    label: str

client = OpenAIClient()

# Maticlib automatically injects formatting instructions and parses the result
response = client.complete(
    input="Analyze this: I love structural documentation!",
    response_model=Sentiment
)

# Access the validated Pydantic object directly
sentiment = response.parsed_output
print(f"{sentiment.label}: {sentiment.score}")